Intelligent channel sensing based secure cross layer cognitive networking for resilient space communication
In this paper, we discuss a novel intelligent channel sensing based secure cross layer cognitive networking architecture for resilient space communication. A cognitive network can accurately, autonomously, intelligently, and rapidly adapt to a continuously/dynamically changing communication environment. We propose to develop a new cognitive networking architecture in the context of space communication for various NASA applications such as SCaN (space communication and navigation) system. Specifically, an intelligent channel sensing engine will sense space communication channel information and interferences including signal and interference detection, RF parameter estimation, signal identification via advanced signal processing techniques such as cyclostationary analysis. Next, artificial intelligence techniques such as neural network and support vector machine are exploited to learn and predict the channel dynamics from past channel sensing data. Such characterization enables optimizing waveforms through combinations of coding, encryption, and modulation before the short communication window becomes available, thereby saving valuable resources (e.g. time). Furthermore, a cross-layer cognitive networking algorithm will be developed to dynamically select and reconfigure network protocols at several layers in varying degrees. Finally, algorithms, instrumentation, methods, and software being used by the cognitive network in decision-making will be protected via i) intelligent malicious behavior detection/prevention and ii) secure hardware where applicable.
& Wang, B.
(2016). Intelligent channel sensing based secure cross layer cognitive networking for resilient space communication. Proceedings of the IEEE National Aerospace Electronics Conference, NAECON, 407-411.